Lead Engineer - Powertrain Data Analytics

Responsibilities & Key Deliverables

Key Tasks and Deliverables

• Analyze and interpret vehicle test data from ICE and EV platforms to derive actionable insights.
• Develop and maintain cloud-based analytics methodologies using MATLAB, Python, and Databricks.
• Design and deploy interactive dashboards and web applications for data visualization and reporting using Power BI and Tableau.
• Collaborate with calibration and testing teams to integrate analytics into vehicle development workflows.
• Support predictive modeling and machine learning initiatives for performance and reliability analysis.

Critical Must-Have Deliverables

• Accurate analysis of drivability and performance test data for ICE and EV platforms.
• Development of robust data analytics pipelines leveraging Python, MATLAB, and cloud platforms.
• Creation of real-time dashboards for vehicle performance monitoring and reporting.
• Integration of analytics into calibration and testing processes to improve efficiency and reliability.

Good-to-Have Deliverables

• Implementation of advanced machine learning models for predictive maintenance and performance optimization.
• Development of simulation models for vehicle systems to support virtual testing.
• Contribution to cross-functional projects involving EV efficiency mapping and fleet durability analysis.

Experience

• 3–5 years of experience in engine/vehicle testing or system simulation.
• 1–2 years of hands-on experience in data analytics and visualization.
• Exposure to ICE and EV architectures, calibration tools, and CAN protocols.

Industry Preferred

Automotive OEMs and Tier-1 suppliers specializing in powertrain development, EV systems, and vehicle testing.

Qualifications

• Bachelor’s or Master’s degree in Mechanical Engineering, Automotive Engineering, Electrical Engineering, or Data Science.
• Certifications in data analytics tools (Python, MATLAB) and cloud platforms (Databricks, Spark) are desirable.

General Requirements

Competencies and Skills

• Vehicle and engine performance analysis, drivability assessment, EV efficiency mapping.
• VCU calibration, emission analysis, fleet durability evaluation.

• MATLAB, Python, Databricks, Spark, Power BI, Tableau, Excel.
• Knowledge of CAN protocols and calibration tools.

• Strong analytical thinking and problem-solving skills.
• Ability to collaborate effectively with cross-functional teams.
• Adaptability to emerging technologies and agile workflows.

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